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OpenML
Task
Supervised Classification on fri_c0_1000_10

Supervised Classification on fri_c0_1000_10

Task 3710 Supervised Classification fri_c0_1000_10 438 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.821, f_measure: 0.7629, kappa: 0.5256, kb_relative_information_score: 431.3394, mean_absolute_error: 0.2908, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.7632, predictive_accuracy: 0.763, prior_entropy: 0.9998, recall: 0.763, relative_absolute_error: 0.5818, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4166, root_relative_squared_error: 0.8332, scimark_benchmark: 942.9518, usercpu_time_millis: 180, usercpu_time_millis_testing: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8076, f_measure: 0.8076, kappa: 0.6168, kb_relative_information_score: 617.8212, mean_absolute_error: 0.191, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.816, predictive_accuracy: 0.809, prior_entropy: 0.9998, recall: 0.809, relative_absolute_error: 0.3821, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.437, root_relative_squared_error: 0.8742, scimark_benchmark: 1312.3073, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8355, f_measure: 0.8358, kappa: 0.6716, kb_relative_information_score: 671.8463, mean_absolute_error: 0.164, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8366, predictive_accuracy: 0.836, prior_entropy: 0.9998, recall: 0.836, relative_absolute_error: 0.3281, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.405, root_relative_squared_error: 0.8101, scimark_benchmark: 938.9967, usercpu_time_millis: 660, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 550,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.837, f_measure: 0.837, kappa: 0.6739, kb_relative_information_score: 673.8472, mean_absolute_error: 0.163, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.837, predictive_accuracy: 0.837, prior_entropy: 0.9998, recall: 0.837, relative_absolute_error: 0.3261, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4037, root_relative_squared_error: 0.8076, scimark_benchmark: 1250.8301, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9116, f_measure: 0.833, kappa: 0.6659, kb_relative_information_score: 518.6764, mean_absolute_error: 0.2561, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.833, predictive_accuracy: 0.833, prior_entropy: 0.9998, recall: 0.833, relative_absolute_error: 0.5124, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3461, root_relative_squared_error: 0.6924, scimark_benchmark: 934.6432, usercpu_time_millis: 150, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.835, f_measure: 0.835, kappa: 0.67, kb_relative_information_score: 669.8454, mean_absolute_error: 0.165, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8351, predictive_accuracy: 0.835, prior_entropy: 0.9998, recall: 0.835, relative_absolute_error: 0.3301, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4062, root_relative_squared_error: 0.8125, scimark_benchmark: 935.5075, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9402, f_measure: 0.867, kappa: 0.7339, kb_relative_information_score: 608.5118, mean_absolute_error: 0.2092, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.867, predictive_accuracy: 0.867, prior_entropy: 0.9998, recall: 0.867, relative_absolute_error: 0.4184, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3126, root_relative_squared_error: 0.6252, scimark_benchmark: 923.6051, usercpu_time_millis: 14430, usercpu_time_millis_testing: 230, usercpu_time_millis_training: 14200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8951, f_measure: 0.8169, kappa: 0.6337, kb_relative_information_score: 510.8099, mean_absolute_error: 0.2578, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8173, predictive_accuracy: 0.817, prior_entropy: 0.9998, recall: 0.817, relative_absolute_error: 0.5157, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3618, root_relative_squared_error: 0.7238, scimark_benchmark: 1350.9691, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9439, f_measure: 0.859, kappa: 0.7179, kb_relative_information_score: 564.9129, mean_absolute_error: 0.2339, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.859, predictive_accuracy: 0.859, prior_entropy: 0.9998, recall: 0.859, relative_absolute_error: 0.468, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3162, root_relative_squared_error: 0.6324, scimark_benchmark: 1361.1055, usercpu_time_millis: 400, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 370,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7868, f_measure: 0.787, kappa: 0.5738, kb_relative_information_score: 573.8007, mean_absolute_error: 0.213, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.787, predictive_accuracy: 0.787, prior_entropy: 0.9998, recall: 0.787, relative_absolute_error: 0.4261, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4615, root_relative_squared_error: 0.9232, scimark_benchmark: 1361.1055,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8587, f_measure: 0.797, kappa: 0.594, kb_relative_information_score: 517.4625, mean_absolute_error: 0.2522, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.7972, predictive_accuracy: 0.797, prior_entropy: 0.9998, recall: 0.797, relative_absolute_error: 0.5045, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3943, root_relative_squared_error: 0.7888, scimark_benchmark: 1073.494, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8324, f_measure: 0.8149, kappa: 0.6297, kb_relative_information_score: 567.9804, mean_absolute_error: 0.2257, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8153, predictive_accuracy: 0.815, prior_entropy: 0.9998, recall: 0.815, relative_absolute_error: 0.4515, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4001, root_relative_squared_error: 0.8003, scimark_benchmark: 1354.2491, usercpu_time_millis: 110, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7706, f_measure: 0.7673, kappa: 0.5394, kb_relative_information_score: 537.7839, mean_absolute_error: 0.231, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.7798, predictive_accuracy: 0.769, prior_entropy: 0.9998, recall: 0.769, relative_absolute_error: 0.4621, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4806, root_relative_squared_error: 0.9614, scimark_benchmark: 1341.5768, usercpu_time_millis: 200, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5422, f_measure: 0.4149, kappa: 0.083, kb_relative_information_score: 67.565, mean_absolute_error: 0.466, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.7393, predictive_accuracy: 0.534, prior_entropy: 0.9998, recall: 0.534, relative_absolute_error: 0.9323, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6826, root_relative_squared_error: 1.3655, scimark_benchmark: 1287.514, usercpu_time_millis: 490, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 410,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8669, f_measure: 0.8125, kappa: 0.6253, kb_relative_information_score: 577.5205, mean_absolute_error: 0.217, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8148, predictive_accuracy: 0.813, prior_entropy: 0.9998, recall: 0.813, relative_absolute_error: 0.434, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3831, root_relative_squared_error: 0.7664, scimark_benchmark: 1358.4523, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6547, f_measure: 0.6549, kappa: 0.3095, kb_relative_information_score: 309.6777, mean_absolute_error: 0.345, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.6549, predictive_accuracy: 0.655, prior_entropy: 0.9998, recall: 0.655, relative_absolute_error: 0.6902, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5874, root_relative_squared_error: 1.1749, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8072, f_measure: 0.807, kappa: 0.6141, kb_relative_information_score: 613.8193, mean_absolute_error: 0.193, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8073, predictive_accuracy: 0.807, prior_entropy: 0.9998, recall: 0.807, relative_absolute_error: 0.3861, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8788, scimark_benchmark: 1353.5686, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4982, f_measure: 0.3434, kb_relative_information_score: -0.006, mean_absolute_error: 0.4998, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.2591, predictive_accuracy: 0.509, prior_entropy: 0.9998, recall: 0.509, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4999, root_relative_squared_error: 1, scimark_benchmark: 1418.5826,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8294, f_measure: 0.8299, kappa: 0.6597, kb_relative_information_score: 627.8499, mean_absolute_error: 0.191, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8301, predictive_accuracy: 0.83, prior_entropy: 0.9998, recall: 0.83, relative_absolute_error: 0.3821, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.397, root_relative_squared_error: 0.794, scimark_benchmark: 1605.6303, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9432, f_measure: 0.861, kappa: 0.7219, kb_relative_information_score: 722.4401, mean_absolute_error: 0.1387, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.861, predictive_accuracy: 0.861, prior_entropy: 0.9998, recall: 0.861, relative_absolute_error: 0.2774, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3585, root_relative_squared_error: 0.717, scimark_benchmark: 927.0753, usercpu_time_millis: 190, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9385, f_measure: 0.876, kappa: 0.7519, kb_relative_information_score: 737.7096, mean_absolute_error: 0.1324, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.876, predictive_accuracy: 0.876, prior_entropy: 0.9998, recall: 0.876, relative_absolute_error: 0.265, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3313, root_relative_squared_error: 0.6626, scimark_benchmark: 945.6434, usercpu_time_millis: 280, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9349, f_measure: 0.877, kappa: 0.7539, kb_relative_information_score: 738.0659, mean_absolute_error: 0.133, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.877, predictive_accuracy: 0.877, prior_entropy: 0.9998, recall: 0.877, relative_absolute_error: 0.2661, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3189, root_relative_squared_error: 0.6379, scimark_benchmark: 941.7954, usercpu_time_millis: 160, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9429, f_measure: 0.871, kappa: 0.742, kb_relative_information_score: 699.1906, mean_absolute_error: 0.1552, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8712, predictive_accuracy: 0.871, prior_entropy: 0.9998, recall: 0.871, relative_absolute_error: 0.3105, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3119, root_relative_squared_error: 0.6239, scimark_benchmark: 923.7642, usercpu_time_millis: 150, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9429, f_measure: 0.871, kappa: 0.742, kb_relative_information_score: 699.1906, mean_absolute_error: 0.1552, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8712, predictive_accuracy: 0.871, prior_entropy: 0.9998, recall: 0.871, relative_absolute_error: 0.3105, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3119, root_relative_squared_error: 0.6239, scimark_benchmark: 894.7455, usercpu_time_millis: 150, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9498, f_measure: 0.8759, kappa: 0.7518, kb_relative_information_score: 735.1765, mean_absolute_error: 0.1339, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8762, predictive_accuracy: 0.876, prior_entropy: 0.9998, recall: 0.876, relative_absolute_error: 0.2679, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3236, root_relative_squared_error: 0.6473, scimark_benchmark: 936.6206, usercpu_time_millis: 720, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 710,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9465, f_measure: 0.867, kappa: 0.7338, kb_relative_information_score: 722.7881, mean_absolute_error: 0.1401, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8671, predictive_accuracy: 0.867, prior_entropy: 0.9998, recall: 0.867, relative_absolute_error: 0.2804, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3281, root_relative_squared_error: 0.6563, scimark_benchmark: 936.7115, usercpu_time_millis: 390, usercpu_time_millis_training: 390,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.93, f_measure: 0.839, kappa: 0.6778, kb_relative_information_score: 668.1177, mean_absolute_error: 0.1682, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8391, predictive_accuracy: 0.839, prior_entropy: 0.9998, recall: 0.839, relative_absolute_error: 0.3366, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3486, root_relative_squared_error: 0.6973, scimark_benchmark: 936.6206, usercpu_time_millis: 170, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8857, f_measure: 0.7965, kappa: 0.5933, kb_relative_information_score: 563.8865, mean_absolute_error: 0.2213, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.7985, predictive_accuracy: 0.797, prior_entropy: 0.9998, recall: 0.797, relative_absolute_error: 0.4428, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3998, root_relative_squared_error: 0.7997, scimark_benchmark: 934.5243, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8296, f_measure: 0.7075, kappa: 0.4321, kb_relative_information_score: 412.0966, mean_absolute_error: 0.2964, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.7488, predictive_accuracy: 0.718, prior_entropy: 0.9998, recall: 0.718, relative_absolute_error: 0.5931, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4573, root_relative_squared_error: 0.9148, scimark_benchmark: 938.4278, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9475, f_measure: 0.875, kappa: 0.7499, kb_relative_information_score: 703.009, mean_absolute_error: 0.1538, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.875, predictive_accuracy: 0.875, prior_entropy: 0.9998, recall: 0.875, relative_absolute_error: 0.3076, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3107, root_relative_squared_error: 0.6214, scimark_benchmark: 936.6206, usercpu_time_millis: 350, usercpu_time_millis_training: 350,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9446, f_measure: 0.868, kappa: 0.7359, kb_relative_information_score: 622.2306, mean_absolute_error: 0.2015, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.868, predictive_accuracy: 0.868, prior_entropy: 0.9998, recall: 0.868, relative_absolute_error: 0.403, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.308, root_relative_squared_error: 0.6161, scimark_benchmark: 947.9494, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9285, f_measure: 0.841, kappa: 0.682, kb_relative_information_score: 538.7453, mean_absolute_error: 0.2466, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8411, predictive_accuracy: 0.841, prior_entropy: 0.9998, recall: 0.841, relative_absolute_error: 0.4934, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3319, root_relative_squared_error: 0.6639, scimark_benchmark: 931.2336, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4982, f_measure: 0.3434, kb_relative_information_score: -0.006, mean_absolute_error: 0.4998, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.2591, predictive_accuracy: 0.509, prior_entropy: 0.9998, recall: 0.509, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4999, root_relative_squared_error: 1, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9119, f_measure: 0.8349, kappa: 0.6703, kb_relative_information_score: 550.8442, mean_absolute_error: 0.2371, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8371, predictive_accuracy: 0.835, prior_entropy: 0.9998, recall: 0.835, relative_absolute_error: 0.4743, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3468, root_relative_squared_error: 0.6937, scimark_benchmark: 934.5243, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9236, f_measure: 0.838, kappa: 0.676, kb_relative_information_score: 566.3143, mean_absolute_error: 0.2288, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8383, predictive_accuracy: 0.838, prior_entropy: 0.9998, recall: 0.838, relative_absolute_error: 0.4578, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.6699, scimark_benchmark: 933.8635, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9156, f_measure: 0.843, kappa: 0.6861, kb_relative_information_score: 581.2625, mean_absolute_error: 0.219, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8436, predictive_accuracy: 0.843, prior_entropy: 0.9998, recall: 0.843, relative_absolute_error: 0.4381, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3401, root_relative_squared_error: 0.6804, scimark_benchmark: 902.4773, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4982, f_measure: 0.3434, kb_relative_information_score: -0.006, mean_absolute_error: 0.4998, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.2591, predictive_accuracy: 0.509, prior_entropy: 0.9998, recall: 0.509, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4999, root_relative_squared_error: 1, scimark_benchmark: 929.566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9285, f_measure: 0.841, kappa: 0.682, kb_relative_information_score: 538.7453, mean_absolute_error: 0.2466, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8411, predictive_accuracy: 0.841, prior_entropy: 0.9998, recall: 0.841, relative_absolute_error: 0.4934, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3319, root_relative_squared_error: 0.6639, scimark_benchmark: 911.0478, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3434, kb_relative_information_score: 17.5417, mean_absolute_error: 0.491, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.2591, predictive_accuracy: 0.509, prior_entropy: 0.9998, recall: 0.509, relative_absolute_error: 0.9823, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.7007, root_relative_squared_error: 1.4017, scimark_benchmark: 929.0255,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8294, f_measure: 0.8299, kappa: 0.6597, kb_relative_information_score: 627.8499, mean_absolute_error: 0.191, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8301, predictive_accuracy: 0.83, prior_entropy: 0.9998, recall: 0.83, relative_absolute_error: 0.3821, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.397, root_relative_squared_error: 0.794, scimark_benchmark: 904.3001, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9142, f_measure: 0.844, kappa: 0.6878, kb_relative_information_score: 273.9161, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.844, predictive_accuracy: 0.844, prior_entropy: 0.9998, recall: 0.844, relative_absolute_error: 0.7776, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4031, root_relative_squared_error: 0.8063, scimark_benchmark: 943.2817, usercpu_time_millis: 1850, usercpu_time_millis_training: 1850,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8225, f_measure: 0.7409, kappa: 0.4817, kb_relative_information_score: 195.689, mean_absolute_error: 0.4198, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.741, predictive_accuracy: 0.741, prior_entropy: 0.9998, recall: 0.741, relative_absolute_error: 0.84, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4367, root_relative_squared_error: 0.8736, scimark_benchmark: 917.7039,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3434, kb_relative_information_score: 17.5417, mean_absolute_error: 0.491, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.2591, predictive_accuracy: 0.509, prior_entropy: 0.9998, recall: 0.509, relative_absolute_error: 0.9823, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.7007, root_relative_squared_error: 1.4017, scimark_benchmark: 917.7039, usercpu_time_millis: 930, usercpu_time_millis_testing: 210, usercpu_time_millis_training: 720,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8355, f_measure: 0.8358, kappa: 0.6716, kb_relative_information_score: 671.8463, mean_absolute_error: 0.164, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8366, predictive_accuracy: 0.836, prior_entropy: 0.9998, recall: 0.836, relative_absolute_error: 0.3281, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.405, root_relative_squared_error: 0.8101, scimark_benchmark: 941.8057, usercpu_time_millis: 760, usercpu_time_millis_testing: 140, usercpu_time_millis_training: 620,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8987, f_measure: 0.878, kappa: 0.7559, kb_relative_information_score: 757.4139, mean_absolute_error: 0.1211, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.878, predictive_accuracy: 0.878, prior_entropy: 0.9998, recall: 0.878, relative_absolute_error: 0.2423, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3439, root_relative_squared_error: 0.6879, scimark_benchmark: 943.6956, usercpu_time_millis: 3090, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 3040,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9251, f_measure: 0.8429, kappa: 0.6857, kb_relative_information_score: 684.1396, mean_absolute_error: 0.1581, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8434, predictive_accuracy: 0.843, prior_entropy: 0.9998, recall: 0.843, relative_absolute_error: 0.3163, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3669, root_relative_squared_error: 0.734, scimark_benchmark: 883.7187, usercpu_time_millis: 1070, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 1060,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8353, f_measure: 0.7553, kappa: 0.5129, kb_relative_information_score: 410.4992, mean_absolute_error: 0.3074, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.7605, predictive_accuracy: 0.756, prior_entropy: 0.9998, recall: 0.756, relative_absolute_error: 0.615, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4185, root_relative_squared_error: 0.8372, scimark_benchmark: 917.1386, usercpu_time_millis: 190, usercpu_time_millis_training: 190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9402, f_measure: 0.859, kappa: 0.7178, kb_relative_information_score: 709.1496, mean_absolute_error: 0.1469, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.859, predictive_accuracy: 0.859, prior_entropy: 0.9998, recall: 0.859, relative_absolute_error: 0.294, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3341, root_relative_squared_error: 0.6682, scimark_benchmark: 935.8986, usercpu_time_millis: 700, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 690,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9113, f_measure: 0.811, kappa: 0.6219, kb_relative_information_score: 489.1482, mean_absolute_error: 0.2714, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.811, predictive_accuracy: 0.811, prior_entropy: 0.9998, recall: 0.811, relative_absolute_error: 0.543, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3504, root_relative_squared_error: 0.7009, scimark_benchmark: 935.8986, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8355, f_measure: 0.8358, kappa: 0.6716, kb_relative_information_score: 671.8463, mean_absolute_error: 0.164, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8366, predictive_accuracy: 0.836, prior_entropy: 0.9998, recall: 0.836, relative_absolute_error: 0.3281, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.405, root_relative_squared_error: 0.8101, scimark_benchmark: 945.6434, usercpu_time_millis: 760, usercpu_time_millis_testing: 130, usercpu_time_millis_training: 630,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8273, f_measure: 0.8276, kappa: 0.6554, kb_relative_information_score: 655.8389, mean_absolute_error: 0.172, mean_prior_absolute_error: 0.4998, number_of_instances: 1000, precision: 0.8297, predictive_accuracy: 0.828, prior_entropy: 0.9998, recall: 0.828, relative_absolute_error: 0.3441, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4147, root_relative_squared_error: 0.8296, scimark_benchmark: 799.2185, usercpu_time_millis: 90, usercpu_time_millis_training: 90,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs